Space weather prediction involves advance forecasting of the magnitude and onset time of major geomagneticstorms on Earth. In this paper, we discuss the development of an artificial neural network-basedmodel to study the precursor leading to intense and moderate geomagnetic storms, following halo coronalmass ejection (CME) and related interplanetary (IP) events. IP inputs were considered within a 5-daytime window after the commencement of storm. The artificial neural network (ANN) model training,testing and validation datasets were constructed based on 110 halo CMEs (both full and partial halo andtheir properties) observed during the ascending phase of the 24th solar cycle between 2009 and 2014. Thegeomagnetic storm occurrence rate from halo CMEs is estimated at a probability of 79%, by this model.

Global Shuttle Radar Topography Mission (SRTM) data products have been widely used in EarthSciences without an estimation of their accuracy and reliability even though large outliers exist in them.The global 1 arc-sec, 30 m resolution, SRTM C-Band (C-30) data collected in February 2000 has beenrecently released (2014–2015) outside North America. We present the first global assessment of thevertical accuracy of C-30 data using Ground Control Points (GCPs) from the International GNSS Service(IGS) Network of high-precision static fiducial stations that define the International Terrestrial ReferenceFrame (ITRF). Large outliers (height error ranging from –1285 to 2306 m) were present in the C-30dataset and 14% of the data were removed to reduce the root mean square error (RMSE) of the datasetfrom ∼187 to 10.3 m which is close to the SRTM goal of an absolute vertical accuracy of RMSE ∼10 m.Globally, for outlier-filtered data from 287 GCPs, the error or difference between IGS and SRTM heightsexhibited a non-normal distribution with a mean and standard error of 6.5 ± 0.5 m. Continent-wise,only Australia, North and South America complied with the SRTM goal. At stations where all the XandC-Band SRTM data were present, the RMSE of the outlier-filtered C-30 data was 11.7 m. However,the RMSE of outlier-included dataset where C- and X-Band data were present was ∼233 m. The resultssuggest that the SRTM data must only be used after regional accuracy analysis and removal of outliers.If used raw, they may produce results that are statistically insignificant with RMSE in 100s of meters.

Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought)for areas where rainfall data are not available or rain gauge stations are sparse. In this study, dailyprecipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validatedagainst daily rain gauge precipitation for the monsoon months (June–September or JJAS) from 2005–2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPHcan detect rain and no-rain events, but they fail to capture the intensity of rainfall.The detection of precipitation amount is strongly dependent on the topography. In the plains areas,TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimatesthe amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capturethe high-intensity rain events but does well with low-intensity rain events in both hilly regions as well asthe plain region. The continuous variable verification method shows better agreement of TRMM rainfallproducts with rain gauge data. TRMM fares better in the prediction of probability of occurrenceof high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies thatTRMM precipitation estimates can be used for flood-related studies only after bias adjustment for thetopography.

Surface level soil moisture from two gridded datasets over India are evaluated in this study. The firstone is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation systembased on Extended Kalman Filter method (EKF), which make use of satellite observation of AdvancedScatterometer (ASCAT) soil wetness index as well as the screen level meteorological observations. Seconddataset is a satellite soil moisture product, produced by National Remote Sensing Centre (NRSC) usingpassive microwave Advanced Microwave Scanning Radiometer 2 measurements. In-situ observations ofsoil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soilmoisture products. The difference between these datasets over India is minimum in the non-monsoonmonths and over agricultural regions. It is seen that the NRSC data is slightly drier (0.05%) and UKMOsoil moisture analysis is relatively wet during southwest monsoon season. Standard AMSR-2 satellitesoil moisture product is used to compare the NRSC and UKMO products. The standard AMSR-2 andUKMO values are closer in monsoon season and AMSR-2 soil moisture is higher than UKMO in allseasons. NRSC and AMSR-2 showed a correlation of 0.83 (significant at 0.01 level). The probabilitydistribution of IMD soil moisture observation peaks at 0.25 m^3/m^3, NRSC at 0.15 m^3/m^3, AMSR-2 at0.25 m3/m3 and UKMO at 0.35 m^3/m^3 during June–September period. Validation results show UKMOanalysis has better correlation with in-situ observations compared to the NRSC and AMSR-2 datasets.The seasonal variation in soil moisture is better represented in UKMO analysis. Underestimation of soilmoisture during monsoon season over India in NRSC data suggests the necessity of incorporating theactual vegetation for a better soil moisture retrieval using passive microwave sensors. Both productshave good agreement over bare soil, shrubs and grassland compared to needle leaf tree, broad leaf treeand urban land cover types.

This paper presents a new algorithm to classify convective clouds and determine their intensity, based oncloud physical properties retrieved from the Spinning Enhanced Visible and Infrared Imager (SEVIRI).The convective rainfall events at 15 min, 4 × 5 km spatial resolution from 2006 to 2012 are analysed overnorthern Algeria. The convective rain classification methodology makes use of the relationship betweencloud spectral characteristics and cloud physical properties such as cloud water path (CWP), cloudphase (CP) and cloud top height (CTH). For this classification, a statistical method based on ‘naiveBayes classifier’ is applied. This is a simple probabilistic classifier based on applying ‘Bayes’ theoremwith strong (naive) independent assumptions. For a 9-month period, the ability of SEVIRI to classifythe rainfall intensity in the convective clouds is evaluated using weather radar over the northern Algeria.The results indicate an encouraging performance of the new algorithm for intensity differentiation ofconvective clouds using SEVIRI data.

Variability in precipitation is critical for the management of water resources. In this study, the researchentropy base concept was applied to investigate spatial and temporal variability of the precipitationduring 1964–2013 in the Songhua River basin of Heilongjiang Province in China. Sample entropy wasapplied on precipitation data on a monthly, seasonally, annually, decade scale and the number of rainydays for each selected station. Intensity entropy and apportionment entropy were used to calculate thevariability over individual year and decade, respectively. Subsequently, Spearman’s Rho and Mann–Kendall tests were applied to observe for trends in the precipitation time series. The statistics of sampledisorder index showed that the precipitation during February (mean 1.09, max. 1.26 and min. 0.80),April (mean 1.12, max. 1.29 and min. 0.99) and July (mean 1.10, max. 1.20 and min. 0.98) contributedsignificantly higher than those of other months. Overall, the contribution of the winter season wasconsiderably high with a standard deviation of 0.10. The precipitation variability on decade basis wasobserved to increase from decade 1964–1973 and 1994–2003 with a mean value of decadal apportionmentdisorder index 0.023 and 0.053, respectively. In addition, the Mann–Kendall test value (1.90) showed asignificant positive trend only at the Shangzhi station.

The Eastern Mediterranean region has been exposed to drought episodes, which have been occurring morefrequently during the last decades. The objective of the present paper is to study the precipitation regimeof the Damascus (Mazzeh) meteoric station by analysing drought characteristics using the StandardizedPrecipitation Index (SPI) and comparing this with the drought in Cyprus. The cumulative droughtconcept is proposed to characterize long-term hydrologic drought, which affects the shallow groundwaterproductivity in terms of quantity and quality. Gamma probability distribution was fitted to the long-termannual precipitation in Damascus from 1918–1919 to 2007–2008 (n = 90 years). Generally, a decreasingtrend of 17% to the mean annual rainfall of Damascus and 13% to the mean annual rainfall of Cypruswas estimated between 1970 and 2000. The SPI identifies three major extended drought periods: (1)9 years of severe drought (1954–1963) with an average 20% precipitation deficit per year compared tothe mean. (2) 8 years of severe drought (1983–1991) with a 27% deficit per year on average. (3) 9 yearsof extreme drought (1993–2002) with a 31% deficit per year on average. The cumulative standardizedprecipitation index (SPI 30) demonstrates positive values for the first period and is indicative of havingno effect on the global water balance. SPI 30 exhibits sensitive equilibrium with near zero values / a nearzero value (±1.5) for the second period. For the third period, however, the SPI 30 decreases below −10indicating an extreme hydrological drought that has negative consequences on the recent groundwaterrecharge. It is required to develop and implement a sustainable groundwater management strategy toreduce long-terms drought risks. Generally, the SPI 30 in Cyprus is parallel to that in Damascus witha 3–5 year delay. Thus, the central zone of the Eastern Mediterranean region is facing big challengesand has been suffering from three decades of moderate to severe hydrological drought (SPI 30 = −5to −10) causing a severe decrease in springs discharges of the region. Therefore, in order to reduce theclimate change effects on water resources, it is necessary to adopt a sustainable proactive managementplan during the frequent severe droughts.

In this paper, multivariate adaptive regression splines (MARS) was developed as a novel soft-computingtechnique for predicting longitudinal dispersion coefficient (DL) in rivers. As mentioned in the literature,experimental dataset related to DL was collected and used for preparing MARS model. Results of MARSmodel were compared with multi-layer neural network model and empirical formulas. To define the mosteffective parameters on DL, the Gamma test was used. Performance of MARS model was assessed bycalculation of standard error indices. Error indices showed that MARS model has suitable performanceand is more accurate compared to multi-layer neural network model and empirical formulas. Results ofthe Gamma test and MARS model showed that flow depth (H) and ratio of the mean velocity to shearvelocity (u/u^∗) were the most effective parameters on the DL.

Ozone is one of the most significant secondary pollutants with numerous negative effects on humanhealth and environment including plants and vegetation. Therefore, more effort is made recently bygovernments and associations to predict ozone concentrations which could help in establishing betterplans and regulation for environment protection. In this study, we use two Artificial Neural Networkbased approaches (MPL and RBF) to develop, for the first time, accurate ozone prediction models, onefor urban and another one for rural area in the eastern part of Croatia. The evaluation of actual againstthe predicted ozone concentrations revealed that MLP and RBF models are very competitive for thetraining and testing data in the case of Kopaˇcki Rit area whereas in the case of Osijek city, MLP showsbetter evaluation results with 9% improvement in the correlation coefficient. Furthermore, subsequentfeature selection process has improved the prediction power of RBF network.

The Nellore Schist Belt (NSB) is a curvilinear Archaean schist belt, approximately 350 km long and
8–50 km wide. The Nellore Schist Belt is considered to be Neoarchean in age and stratigraphically
NSB is classified as the western Udayagiri group (dominated by metasediments) and underlying eastern
Vinjamuru group (dominated by metabasalts). There is a long controversy regarding the contact relationship
between Udayagiri and Vinjamuru groups. Earlier researchers regarded the contact between two
groups as tectonic on the basis of metamorphism. A shear zone and a possible thrust contact between
the two groups have also been reported. On the basis of present study, an NNW–SSE trending, westerly
dipping inclined transpressional zone is found at the contact between Udayagiri and Vinjamuru groups
in the central western part of the NSB. Kinematic analysis of both the hanging wall and foot wall of the
westerly dipping thrust zone shows presence of strong S1 schistosity, shear bands and S-C fabric in both
strike and dip section along with east-verging overturned fold, westerly dipping inverted beds, suggesting
partitioning of non-coaxial deformation in strike-slip and dip-slip component along with a pure shear
component. Strike-slip is more prominent in the northern part of the contact than the southern part. The
presence of steep to moderate northerly plunging non-orthogonal stretching/mineral elongation lineation
all along the contact and clockwise shift of plot of the same in stereo net from its orthogonal position
and presence of other kinematic indicators in plan suggests a right lateral strike-slip component. As a
whole, it is suggested that Udayagiri group is thrusted over Vinjamuru group along a westerly dipping
thrust plane with a right lateral strike-slip motion and simultaneous E–W contraction.

Future earthquake potential in the Bohai–Zhangjiakou Seismotectonic Zone (BZSZ) in North Chinadeserves close attention. Tectonic stress accumulation state is an important indicator for earthquakes;therefore, this study aims to analyse the stress accumulation state in the BZSZ via three-dimensionalvisco-elastic numerical modelling. The results reveal that the maximum shear stress in the BZSZ increasesgradually as the depth increases, and the stress range is wider in the lower layer. In the upper layer, themaximum shear stress is high in the Zhangjiakou area, whereas in the lower layer, relatively high valuesoccur in the Penglai–Yantai area, which may be affected by the depth of the Moho surface. Besides,weak fault zones will be easily fractured when the maximum shear stress is not sufficiently high due totheir low strengths, resulting in earthquakes. Therefore, based on the modelling results, the upper layerof the Zhangjiakou area and the lower layer of the Penglai–Yantai area in the BZSZ in North China aremore likely to experience earthquakes.

Phulad Shear Zone (PSZ) of Delhi Fold Belt in Rajasthan is a northeasterly striking ductile shear zonewith a well developed mylonitic foliation (035/70E) and a downdip stretching lineation. The deformationin the PSZ has developed in a transpressional regime with thrusting sense of movement. The northeasternunit, i.e., the hanging wall contains a variety of rocks namely calc-silicates, pelites and amphibolites andthe southwestern unit, i.e., the footwall unit contains only granitic rocks. Systematic investigation ofthe granites of the southwestern unit indicate a gradual change in the intensity of deformation from adistance of about 1 km west of the shear zone to the shear zone proper. The granite changes from weaklydeformed granite to a mylonite/ultramylonite as we proceed towards the PSZ. The weakly deformedgranite shows a crude foliation with the same attitude of mylonitic foliation of the PSZ. Microscopicstudy reveals the incipient development of C and S fabric with angle between C and S varying from15◦ to 24◦. The small angle between the C and S fabric in the least deformed granite variety indicatesthat the deformation has strong pure shear component. At a distance of about 1 m away from the PSZ,there is abrupt change in the intensity of deformation. The granite becomes intensely foliated with astrong downdip lineation and the rock becomes a true mylonite. In mesoscopic scale, the granite showsstretched porphyroclasts in both XZ and YZ sections indicating a flattening type of deformation. Theangle between the C and S fabric is further reduced and finally becomes nearly parallel. In most places,S fabric is gradually replaced by C fabric. Calculation of sectional kinematic vorticity number (Wn) fromthe protomylonitic and mylonite/ultramylonite granites varies from 0.3 ± 0.03 to 0.55 ± 0.04 indicatinga strong component of pure shear. The similarity of the geometry of structures in the PSZ and thegranites demonstrates that the deformation of the two units is broadly synchronous and the deformationin both the units is transpressional.

This study presents the geochemical characteristics of granitic rocks located on the northern margin of Chotanagpur Gneissic Complex (CGC), exposed in parts of Gaya district, Bihar and discusses thepossible petrogenetic process and source characteristics. These granites are associated with BarabarAnorthosite Complex and Neo-proterozoic Munger–Rajgir group of rocks. The granitic litho-units identifiedin the field are grey, pink and porphyritic granites. On the basis of geochemical and petrographiccharacteristics, the grey and pink granites were grouped together as GPG while the porphyritic graniteswere named as PG. Both GPG and PG are enriched in SiO_2, K_2O, Na_2O, REE (except Eu), Rb,Ba, HFSE (Nb, Y, Zr), depleted in MgO, CaO, Sr and are characterised by high Fe^* values, Ga/Alratios and high Zr saturation temperatures (GPG_{avg} ∼ 861^◦C and PG_{avg} ∼ 835^◦C). The REE patternsfor GPG are moderately fractionated with an average (La/Yb)_N ∼ 4.55 and Eu/Eu^* ∼0.58, than PGwhich are strongly fractionated with an average (La/Yb)_N ∼ 31.86 and Eu/Eu^* ∼0.75. These featuresindicate that the granites have an A-type character. On the basis of geochemical data, we conclude that the granites are probably derived from a predominant crustal source with variable mantle involvementin a post-collisional setting.

The northwestern Guizhou in the Yangtze Craton of south China has a tremendous potential of shale gas resource. In this paper, we present results from major and trace elements, total organic carbon, mineralogical composition analysis and petrophysical parameters to characterise shale weathering features. Further, the differences of black shale between underground and outcrops have also been presented to examine the changes of black shale after weathering. Our results show that the trace elements of shale have varying degrees of loss in the weathering leaching process, both in Niutitang shale and Longmaxi shale, the loss of B, V, Ni, Cu, Zn and Ba is obvious, but the element migration quantity in the formeris greater than in the latter. Decomposition of minerals such as pyrite, feldspar and calcite result in the leaching of Na, Ca, Mg and Fe. The loss rate of total organic carbon (TOC) in black shales ranges from 18% to 70% with an average of 43%; moreover, the loss of organic carbon in samples with high TOC contentis larger than in those samples with low TOC content. Results following the testing of porosity and permeability show that porosity increases significantly after weathering but permeability changes little. Furthermore, the increment of porosity is greater in the Niutitang shale (with more sulphide minerals) than in the Longmaxi shale, suggesting that the oxidation of sulphide minerals may have led to the formationof an acidic environment, causing the other minerals in the black shale to weather more quickly, thus resulting in increased porosity. The content of clay minerals in the core samples is slightly lesser than the outcrop samples, but the TOC content in the core samples is greater and has a larger specific surface area. This suggest that the TOC content played a decisive role on the specific surface area of shale. In addition, changes in the black shale caused by the weathering process mainly depend on the mineral composition and the TOC content in shale. In this study, we try to establish relations between outcrop samples and core samples, in order to better understand the underground characteristics of shale reservoir.

Fossil leaflet impression described here as a new species Rourea miocaudata sp. nov., showing close resemblance with the modern leaflets of Rourea caudata Planch. (Connaraceae R. Br.), has been recorded from the lower part of the Siwalik sediments (Dafla Formation, middle–upper Miocene) exposed at the road-cutting section of Pinjoli area in West Kameng district, Arunachal Pradesh. The importantmorphological characters of the fossil are its narrow elliptic leaflet, cuneate base, long caudate apex, entire margin, eucamptodromous to brochidodromous secondary veins, presence of intersecondary veins, percurrent and reticulate tertiary veins and orthogonally reticulate quaternary veins. This is the first authentic record of the occurrence of leaflet comparable to R. caudata of Connaraceae from the Cenozoic sediments of India and abroad. At present R. caudata does not grow in India and is restricted only in southeast Asia especially in China and Myanmar. This taxon probably migrated to these southeast Asian regions after lower Siwalik sedimentation (middle–upper Miocene) due to climatic change causedby post-Miocene orogenic movement of the Himalaya. The recovery of this species and other earlierdescribed evergreen taxa from the same formation, suggests the existence of a tropical, warm and humid climatic conditions during the depositional period.